Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "92" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460015 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.436405 | 0.000478 | 10.998419 | 0.488045 | 5.866770 | 1.602019 | 0.240249 | 0.563541 | 0.0369 | 0.6089 | 0.4091 | nan | nan |
| 2460014 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.858078 | -0.162907 | 8.317158 | 0.481651 | 8.851156 | 2.686416 | -0.181853 | 0.139275 | 0.0342 | 0.5826 | 0.3983 | nan | nan |
| 2460013 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.231320 | -0.114641 | 11.081363 | 0.394627 | 6.001100 | 1.563001 | 0.857867 | 1.179117 | 0.0352 | 0.6103 | 0.4131 | nan | nan |
| 2460012 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.491384 | -0.118926 | 10.850123 | 0.192032 | 6.499906 | 1.820710 | 0.730848 | 0.965395 | 0.0371 | 0.6113 | 0.4015 | nan | nan |
| 2460011 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.875173 | 0.095193 | 14.442029 | 0.026565 | 13.559771 | 3.794683 | 0.928530 | 1.137715 | 0.0368 | 0.6199 | 0.4042 | nan | nan |
| 2460010 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 12.846566 | -0.099655 | 11.603324 | 0.449844 | 9.266480 | 1.604988 | 0.709140 | 0.978551 | 0.0388 | 0.6357 | 0.4154 | nan | nan |
| 2460009 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.817608 | 0.133422 | 12.948742 | 0.368674 | 7.359217 | 2.147367 | 0.335558 | 1.080122 | 0.0364 | 0.6339 | 0.4121 | nan | nan |
| 2460008 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 14.330900 | 0.057128 | 14.163751 | 0.442495 | 6.678149 | 0.875798 | 4.312210 | 1.024945 | 0.0388 | 0.6852 | 0.4277 | nan | nan |
| 2460007 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.600793 | 0.281086 | 11.063786 | 0.586948 | 5.956730 | 1.557546 | 0.990822 | 0.999872 | 0.0367 | 0.6437 | 0.4119 | nan | nan |
| 2459999 | RF_maintenance | 0.00% | 98.91% | 98.83% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.2885 | 0.3448 | 0.2501 | nan | nan |
| 2459998 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 9.009497 | 0.294702 | 9.464257 | 0.520166 | 8.056998 | 2.074046 | 0.508294 | 1.016891 | 0.0343 | 0.6397 | 0.4308 | nan | nan |
| 2459997 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 9.867865 | 0.172172 | 10.037188 | 0.549031 | 7.777694 | 1.573760 | 0.991079 | 1.412118 | 0.0366 | 0.6538 | 0.4441 | nan | nan |
| 2459996 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.950466 | 0.392796 | 12.614316 | 0.607180 | 7.329208 | 1.145085 | 0.029985 | 1.446945 | 0.0353 | 0.6493 | 0.4460 | nan | nan |
| 2459995 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.165658 | 0.408542 | 11.691416 | 0.234230 | 8.128907 | 1.946094 | -0.021106 | 0.377014 | 0.0409 | 0.6541 | 0.4402 | nan | nan |
| 2459994 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.759189 | 0.464463 | 10.084639 | 0.442809 | 7.825026 | 1.554491 | -0.037287 | 0.196612 | 0.0362 | 0.6476 | 0.4403 | nan | nan |
| 2459993 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.892378 | 0.352765 | 9.363809 | 0.300571 | 10.264172 | 1.705533 | 0.420067 | 0.201158 | 0.0323 | 0.6557 | 0.4255 | nan | nan |
| 2459991 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 12.723075 | 15.838854 | 9.925850 | 10.555534 | 9.262463 | 10.818587 | -0.128622 | 0.443725 | 0.0267 | 0.0253 | 0.0015 | nan | nan |
| 2459990 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 10.332027 | 13.045937 | 9.715500 | 10.247636 | 9.158447 | 11.090332 | -0.215434 | 0.312485 | 0.0270 | 0.0254 | 0.0016 | nan | nan |
| 2459989 | RF_maintenance | 100.00% | 97.19% | 97.30% | 0.05% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | 0.6057 | 0.5935 | 0.2652 | nan | nan |
| 2459988 | RF_maintenance | 100.00% | 0.11% | 20.92% | 0.00% | - | - | 38.705664 | 47.865426 | 0.409067 | 1.515241 | 6.025811 | 5.257177 | 1.360258 | 7.521900 | 0.2907 | 0.2495 | 0.0690 | nan | nan |
| 2459987 | RF_maintenance | 100.00% | 0.00% | 17.83% | 0.00% | - | - | 32.419295 | 39.488249 | 0.488137 | 1.728107 | 4.065137 | 3.591663 | 0.220663 | 9.000046 | 0.2959 | 0.2576 | 0.0681 | nan | nan |
| 2459986 | RF_maintenance | 100.00% | 0.00% | 12.15% | 0.00% | - | - | 39.189754 | 48.027187 | 0.529168 | 1.717462 | 5.832803 | 5.104848 | 3.105854 | 9.362757 | 0.3308 | 0.2852 | 0.0734 | nan | nan |
| 2459985 | RF_maintenance | 100.00% | 0.00% | 16.81% | 0.00% | - | - | 37.042834 | 46.386381 | 0.541096 | 1.658985 | 3.520750 | 3.989963 | 1.578246 | 10.290890 | 0.2892 | 0.2471 | 0.0701 | nan | nan |
| 2459984 | RF_maintenance | 100.00% | 0.00% | 4.38% | 0.00% | - | - | 35.444619 | 44.363303 | 0.644535 | 0.606764 | 7.839015 | 6.979963 | 1.263903 | 1.979031 | 0.3128 | 0.2777 | 0.0649 | nan | nan |
| 2459983 | RF_maintenance | 100.00% | 0.00% | 6.81% | 0.00% | - | - | 35.384593 | 39.703273 | 0.697991 | 1.572066 | 4.874681 | 5.332012 | 10.193036 | 9.047531 | 0.3445 | 0.2950 | 0.0670 | nan | nan |
| 2459982 | RF_maintenance | 100.00% | 0.00% | 1.08% | 0.00% | - | - | 28.576152 | 26.418410 | 1.023870 | 1.703887 | 3.398832 | 3.064986 | 0.624611 | 1.440674 | 0.3858 | 0.3333 | 0.0672 | nan | nan |
| 2459981 | RF_maintenance | 100.00% | 0.00% | 15.94% | 0.00% | - | - | 32.437436 | 35.108391 | 0.455152 | 1.503455 | 6.065584 | 5.427234 | 0.600344 | 7.369236 | 0.2873 | 0.2485 | 0.0641 | nan | nan |
| 2459980 | RF_maintenance | 100.00% | 0.00% | 4.16% | 0.00% | - | - | 30.292372 | 32.337948 | 0.246603 | 1.318830 | 6.013201 | 4.376556 | 2.521162 | 3.982186 | 0.3515 | 0.3062 | 0.0618 | nan | nan |
| 2459979 | RF_maintenance | 100.00% | 0.00% | 20.77% | 0.00% | - | - | 33.409435 | 36.599523 | 0.203972 | 1.295104 | 5.073811 | 4.189802 | 0.411030 | 7.376461 | 0.2814 | 0.2450 | 0.0648 | nan | nan |
| 2459978 | RF_maintenance | 100.00% | 0.00% | 24.32% | 0.00% | - | - | 34.027205 | 36.417046 | 0.249032 | 1.349654 | 5.209606 | 4.437401 | 1.476318 | 11.969837 | 0.2751 | 0.2404 | 0.0638 | nan | nan |
| 2459977 | RF_maintenance | 100.00% | 0.00% | 17.50% | 0.00% | - | - | 33.359548 | 36.301419 | 0.403196 | 1.476064 | 11.552886 | 7.701963 | 10.840716 | 7.372787 | 0.2860 | 0.2464 | 0.0617 | nan | nan |
| 2459976 | RF_maintenance | 100.00% | 0.00% | 20.32% | 0.00% | - | - | 33.787633 | 36.128004 | 0.387816 | 1.447151 | 4.834486 | 4.317082 | 0.825420 | 9.051559 | 0.2881 | 0.2479 | 0.0665 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Shape | 11.436405 | 0.000478 | 11.436405 | 0.488045 | 10.998419 | 1.602019 | 5.866770 | 0.563541 | 0.240249 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Shape | 10.858078 | 10.858078 | -0.162907 | 8.317158 | 0.481651 | 8.851156 | 2.686416 | -0.181853 | 0.139275 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Shape | 11.231320 | 11.231320 | -0.114641 | 11.081363 | 0.394627 | 6.001100 | 1.563001 | 0.857867 | 1.179117 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Power | 10.850123 | 10.491384 | -0.118926 | 10.850123 | 0.192032 | 6.499906 | 1.820710 | 0.730848 | 0.965395 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Power | 14.442029 | 11.875173 | 0.095193 | 14.442029 | 0.026565 | 13.559771 | 3.794683 | 0.928530 | 1.137715 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Shape | 12.846566 | 12.846566 | -0.099655 | 11.603324 | 0.449844 | 9.266480 | 1.604988 | 0.709140 | 0.978551 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Power | 12.948742 | 11.817608 | 0.133422 | 12.948742 | 0.368674 | 7.359217 | 2.147367 | 0.335558 | 1.080122 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Shape | 14.330900 | 0.057128 | 14.330900 | 0.442495 | 14.163751 | 0.875798 | 6.678149 | 1.024945 | 4.312210 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Power | 11.063786 | 10.600793 | 0.281086 | 11.063786 | 0.586948 | 5.956730 | 1.557546 | 0.990822 | 0.999872 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Power | 9.464257 | 9.009497 | 0.294702 | 9.464257 | 0.520166 | 8.056998 | 2.074046 | 0.508294 | 1.016891 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Power | 10.037188 | 9.867865 | 0.172172 | 10.037188 | 0.549031 | 7.777694 | 1.573760 | 0.991079 | 1.412118 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Power | 12.614316 | 10.950466 | 0.392796 | 12.614316 | 0.607180 | 7.329208 | 1.145085 | 0.029985 | 1.446945 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Power | 11.691416 | 11.165658 | 0.408542 | 11.691416 | 0.234230 | 8.128907 | 1.946094 | -0.021106 | 0.377014 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Shape | 10.759189 | 10.759189 | 0.464463 | 10.084639 | 0.442809 | 7.825026 | 1.554491 | -0.037287 | 0.196612 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Shape | 11.892378 | 11.892378 | 0.352765 | 9.363809 | 0.300571 | 10.264172 | 1.705533 | 0.420067 | 0.201158 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 15.838854 | 12.723075 | 15.838854 | 9.925850 | 10.555534 | 9.262463 | 10.818587 | -0.128622 | 0.443725 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 13.045937 | 13.045937 | 10.332027 | 10.247636 | 9.715500 | 11.090332 | 9.158447 | 0.312485 | -0.215434 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 47.865426 | 47.865426 | 38.705664 | 1.515241 | 0.409067 | 5.257177 | 6.025811 | 7.521900 | 1.360258 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 39.488249 | 32.419295 | 39.488249 | 0.488137 | 1.728107 | 4.065137 | 3.591663 | 0.220663 | 9.000046 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 48.027187 | 48.027187 | 39.189754 | 1.717462 | 0.529168 | 5.104848 | 5.832803 | 9.362757 | 3.105854 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 46.386381 | 46.386381 | 37.042834 | 1.658985 | 0.541096 | 3.989963 | 3.520750 | 10.290890 | 1.578246 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 44.363303 | 35.444619 | 44.363303 | 0.644535 | 0.606764 | 7.839015 | 6.979963 | 1.263903 | 1.979031 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 39.703273 | 35.384593 | 39.703273 | 0.697991 | 1.572066 | 4.874681 | 5.332012 | 10.193036 | 9.047531 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | ee Shape | 28.576152 | 28.576152 | 26.418410 | 1.023870 | 1.703887 | 3.398832 | 3.064986 | 0.624611 | 1.440674 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 35.108391 | 35.108391 | 32.437436 | 1.503455 | 0.455152 | 5.427234 | 6.065584 | 7.369236 | 0.600344 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 32.337948 | 32.337948 | 30.292372 | 1.318830 | 0.246603 | 4.376556 | 6.013201 | 3.982186 | 2.521162 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 36.599523 | 33.409435 | 36.599523 | 0.203972 | 1.295104 | 5.073811 | 4.189802 | 0.411030 | 7.376461 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 36.417046 | 36.417046 | 34.027205 | 1.349654 | 0.249032 | 4.437401 | 5.209606 | 11.969837 | 1.476318 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 36.301419 | 33.359548 | 36.301419 | 0.403196 | 1.476064 | 11.552886 | 7.701963 | 10.840716 | 7.372787 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 92 | N10 | RF_maintenance | nn Shape | 36.128004 | 36.128004 | 33.787633 | 1.447151 | 0.387816 | 4.317082 | 4.834486 | 9.051559 | 0.825420 |